Variable and constraint reduction techniques for the temporal bin packing problem with fire-ups

The aim of this letter is to design and computationally test several improvements for the compact integer linear programming (ILP) formulations of the temporal bin packing problem with fire-ups (TBPP-FU). This problem is a challenging generalization of the classical bin packing problem in which the items, interpreted as jobs of given weight, are active only … Read more

The value of stochastic crowd resources and strategic location of mini-depots for last-mile delivery: A Benders decomposition approach

Crowd-shipping is an emergent solution to avoid the negative effects caused by the growing demand for last-mile delivery services. Previous research has studied crowd-shipping typically at an operational planning level. However, the study of support infrastructure within a city logistics framework has been neglected, especially from a strategic perspective. We investigate a crowd-sourced last-mile parcel … Read more

A Benders-type Approach for Robust Optimization of Kidney Exchanges under Full Recourse

The goal of kidney exchange programs is to match recipients with a willing but incompatible donor with another compatible donor, so as to maximize total (weighted) transplants. There is significant uncertainty in this process, as planned transplants may be cancelled for a variety of reasons. Planning exchanges while considering failures, and options for recourse, is … Read more

An order aggregation and scheduling problem for meal delivery

We address a single-machine scheduling problem motivated by a last-mile-delivery setting for a food company. Customers place orders, each characterized by a delivery point (customer location) and an ideal delivery time. An order is considered on time if it is delivered to the customer within a time window given by the ideal delivery time ± … Read more

Efficient Algorithms for Multi-Threaded Interval Scheduling with Machine Availabilities

In the known Interval Scheduling Problem with Machine Availabilities (ISMA), each machine has a contiguous availability interval and each job has a specific time interval which has to be scheduled. The objective is to schedule all jobs such that the machines’ availability intervals are respected or to decide that there exists no such schedule. We … Read more

A Scalable Lower Bound for the Worst-Case Relay Attack Problem on the Transmission Grid

We consider a bilevel attacker-defender problem to find the worst-case attack on the relays that control transmission grid components. The attacker infiltrates some number of relays and renders all of the components connected to them inoperable, with the goal of maximizing load shed. The defender responds by minimizing the resulting load shed, re-dispatching using a … Read more

The vehicle allocation problem: alternative formulation and branch-and-price method

The Vehicle Allocation Problem (VAP) consists of repositioning empty vehicles across a set of terminals over a given planning horizon so as to maximize the profits generated from serving demand for transportation of goods between pair of terminals. This problem has been classically modeled using an extended space-time network which captures the staging of the … Read more

Two-Stage Robust Telemedicine Assignment Problem with Uncertain Service Duration and No-Show Behaviours

The current pandemic of COVID-19 has caused significant strain on medical center resources, which are the main places to provide the rapid response to COVID-19 through the adoption of telemedicine. Thus healthcare managers must make an effective assignment plan for the patients and telemedical doctors when providing telemedicine services. Motivated by this, we present the … Read more

A MILP Approach to DRAM Access Worst-Case Analysis

The Dynamic Random Access Memory (DRAM) is among the major points of contention in multi-core systems. We consider a challenging optimization problem arising in worst-case performance analysis of systems architectures: computing the worst-case delay (WCD) experienced when accessing the DRAM due to the interference of contending requests. The WCD is a crucial input for micro-architectural … Read more

Fleet planning under demand uncertainty: a reinforcement learning approach

This work proposes a model-free reinforcement learning approach to learn a long-term fleet planning problem subjected to air-travel demand uncertainty. The aim is to develop a dynamic fleet policy that adapts over time by intermediate assessments of the states. A Deep Q-network is trained to estimate the optimal fleet decisions based on the airline and … Read more